Beware of biases in machine learning: One CTO explains why it happens

Computers are only as good, or as bad, as the people who program them. And it turns out that many individuals who create machine learning algorithms are presumably and unintentionally building in race and gender bias. In part one of a two-part interview, Richard Sharp, CTO of predictive marketing company Yieldify, explains how it happens. The Enterprisers Project (TEP): Machines are genderless, have no race, and are in and of themselves free of bias. How does bias creep in? Sharp: To understand how bias creeps in you first need to understand the difference between programming in the traditional sense and machine learning. With programming in the traditional sense, a programmer analyses a problem and comes up with an algorithm to solve it (basically an explicit sequence of rules and steps).…